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PERCOM
2007
ACM
14 years 7 months ago
Macro Programming through Bayesian Networks: Distributed Inference and Anomaly Detection
Macro programming a distributed system, such as a sensor network, is the ability to specify application tasks at a global level while relying on compiler-like software to translat...
Marco Mamei, Radhika Nagpal
LOCA
2007
Springer
14 years 1 months ago
Inferring the Everyday Task Capabilities of Locations
Abstract. People rapidly learn the capabilities of a new location, without observing every service and product. Instead they map a few observations to familiar clusters of capabili...
Patricia Shanahan, William G. Griswold
ICPP
1999
IEEE
13 years 11 months ago
SLC: Symbolic Scheduling for Executing Parameterized Task Graphs on Multiprocessors
Task graph scheduling has been found effective in performance prediction and optimization of parallel applications. A number of static scheduling algorithms have been proposed for...
Michel Cosnard, Emmanuel Jeannot, Tao Yang
ICIP
2005
IEEE
14 years 9 months ago
Variable module graphs: a framework for inference and learning in modular vision systems
We present a novel and intuitive framework for building modular vision systems for complex tasks such as surveillance applications. Inspired by graphical models, especially factor...
Amit Sethi, Mandar Rahurkar, Thomas S. Huang
EUROPAR
2003
Springer
14 years 19 days ago
FOBS: A Lightweight Communication Protocol for Grid Computing
The advent of high-performance networks in conjunction with low-cost, powerful computational engines has made possible the development of a new set of technologies termed computat...
Phillip M. Dickens